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Samuel Workman, Ph.D.
I am a political scientist working at the intersection of public policy, data science, and statistics. I specialize in public policy, the bureaucracy, regulatory politics, and statistics. My interests involve text-as-data, machine learning, and statistical modeling, especially classificationj stochastic processes, and maximum likelihood methods. I teach courses in public policy, agenda setting, regulatory policy, and statistics. My current academic projects examine congressional bureaucracies, the regulatory politics of education policy, and agenda setting in food policy.
I also provide statistical consulting in the private sector, specializing in the grocery floral category. My work focuses on data-driven decision-making and management, custom reporting, and data-informed programming.
Skills & Experience
- Policy research, data management, statistical analysis & modeling, presentation, reporting & data visualization, machine learning
- Project Management, grant writing, team leadership & coordination, public speaking
- Market, sales, and inventory analysis, reporting, and visualization, data-driven decision-making and management
- Languages: , , SAS, SPSS, VBA, SQL, Markdown, CSS, HTML (limited)
- Applications: Rstudio, WinEdt, Beamer, binb, xaringan, MS Word, MS Excel, MS PowerPoint, SQLite, MS Access
Academic Positions
Associate Professor of Political Science
The University of Oklahoma Norman, OK USA- Faculty Affiliate, National Institute for Risk & Resilience
- Faculty Member, Big Data & Statistics Working Group
- Faculty Affiliate, The Comparative Agendas Project, University of Texas
Assistant Professor of Political Science
The University of Oklahoma Norman, OK USA- Faculty Affiliate, Center for Risk & Crisis Management
- Faculty Affiliate, Center for Intelligence & National Security
Lecturer in American Politics
Sciences Po Bordeaux, FRAssistant Professor of Government
The University of Texas at Austin Austin, TX USA- Associate Director, Policy Agendas Project